3D seismic acquisition

ABSTRACT

Disclosed are methods of marine 3D seismic data acquisition that do not require compensation for winds and currents.

PRIOR RELATED APPLICATIONS

This application is a non-provisional application which claims benefitunder 35 USC § 119(e) to U.S. Provisional Application Ser. No.62/233,661 filed Sep. 28, 2015, entitled “3D SEISMIC ACQUISITION,” whichis incorporated herein in its entirety.

FEDERALLY SPONSORED RESEARCH STATEMENT

Not applicable.

FIELD OF THE DISCLOSURE

The disclosure generally relates to marine seismic data acquisition.

BACKGROUND OF THE DISCLOSURE

Seismic surveys have become the primary tool of exploration companies inthe continental United States, both onshore and offshore. As an example,an onshore seismic survey is conducted by creating a shock wave—aseismic wave—on or near the surface of the ground along a predeterminedline, using an energy source. The seismic wave travels into the earth,is reflected by subsurface formations, and returns to the surface whereit is recorded by receivers called geophones—similar to microphones. Byanalyzing the time it takes for the seismic waves to reflect off ofsubsurface formations and return to the surface, a geophysicist can mapsubsurface formations and anomalies and predict where oil or gas may betrapped in sufficient quantities for exploration activities.

Until relatively recently, seismic surveys were conducted along a singleline on the ground, and their analysis created a two-dimensional pictureakin to a slice through the earth beneath that line, showing thesubsurface geology along that line. This is referred to astwo-dimensional or 2D seismic data.

Currently, almost all oil and gas exploratory wells are preceded by 3Dseismic surveys. The basic method of testing is the same as for 2D, butinstead of a single line of energy source points and receiver points,the source points and receiver points onshore are commonly laid out in agrid across the property. The resulting recorded reflections received ateach receiver point come from all directions, and sophisticated computerprograms can analyze this data to create a three-dimensional image ofthe subsurface.

Conceptually, 3D surveys are acquired by laying out energy source pointsand receiver points in a grid over the area to be surveyed. The receiverpoints—to record the reflected vibrations from the source points—arecommonly laid down in parallel lines (receiver lines), and the sourcepoints are laid out in parallel lines that are typically approximatelyperpendicular to the receiver lines. Although orthogonal layouts arepreferred, non-orthogonal layouts are sometimes used as well. Thespacing of the source and receiver points is determined by the designand objectives of the survey. They may be several hundred feet apart, oras close as 15 feet.

In marine seismic surveys the survey design is a little different, andinstead of a static set of lines, a vessel tows behind it a series ofstreamers, each having a series of hydrophones along its length. Seee.g., FIG. 1A and FIG. 1B. Also towed behind the vessel are one or moreseismic sources.

A variety of seismic sources are available for marine applications,including water guns (20-150 Hz), Air Gun (10-150 Hz), Sparkers (50-4000Hz), Boomers (30-300 Hz), and Chirp Systems (500 Hz-12 kHz, 2-7 kHz,4-24 kHz, 3.5 kHz, and 200 kHz), but air guns are by far the mostcommon.

The streamers also have depth control “birds” programmed to pivot theirwings in response to hydrostatic pressure, thus keeping the streamers ata constant depth, as well as “paravanes” to minimize lateral deviation,described in more detail below. One of the most critical elements of 3Dmarine seismic systems is positioning. Thus, the vessel also tows one ormore tail-buoys that house a differential global positioning receiverused to accurately position each of the hydrophones and additionalnavigation pods (GPS units and transceivers) are located on theparavanes, gun arrays and pretty much any other location that one canmount them above the surface of the water. Also, noise attenuationalgorithms are now available (see e.g., Q-marine single sensortechnology) that allow the collection of useful data, even when sailingin curves.

A seismic vessel with 2 sources and towing a single streamer is known asa Narrow-Azimuth Towed Streamer (aka “NAZ” or “NATS”). By the early2000s, it was accepted that this type of acquisition was useful forinitial exploration, but inadequate for development and production, inwhich wells had to be accurately positioned. This led to the developmentof the Multi-Azimuth Towed Streamer or “MAZ,” which tried to break thelimitations of the linear acquisition pattern of a NATS survey byacquiring a combination of NATS surveys at different azimuths (see FIGS.2A-2B). This successfully delivered increased illumination of thesubsurface and a better signal to noise ratio.

The seismic properties of salt poses an additional problem for marineseismic surveys, as it attenuates seismic waves and its structurecontains overhangs that are difficult to image. This led to anothervariation on the NATS survey type, the wide-azimuth towed streamer (aka“WAZ” or “WATS”), which was first tested on the Mad Dog field in 2004.See FIG. 3. This type of survey involved a single vessel towing a set of8 streamers and two additional vessels towing seismic sources that werelocated at the start and end of the last receiver line (see diagram).This configuration was “tiled” 4 times, with the receiver vessel movingfurther away from the source vessels each time and eventually creatingthe effect of a survey with 4 times the number of streamers. The endresult was a seismic dataset with a larger range of wider azimuths,delivering a breakthrough in seismic imaging.

Another common acquisition pattern for 3D seismic marine surveys is the“racetrack” vessel pattern, wherein the survey has a single lineorientation (or “survey azimuth”), and a long, narrow spread ofstreamers are towed by a single vessel. Typically, a vessel equippedwith one or two airgun sources and towing 8-10 streamers travels in astraight line through the survey area. When it reaches the edges of thesurvey area, it continues in a straight line for one half the length ofa streamer then turns in a wide arc to travel in a straight line backand parallel to the first run. With each subsequent run, the racetracklike course is displaced laterally from the last run, until the entirearea has been covered.

The racetrack pattern is shown FIG. 4, wherein the acquisition pathfollows a straight line (blue arrow) then turns 180° to acquire data inthe opposite direction (orange arrow). No data are normally recordedduring line turns (black) because the streamers do not maintain theirlateral separation during turns and the position of the receivers cannotbe accurately calculated. Further, there is known to be increased noiseduring turns due to dragging the streamer through the water somewhatsideways.

Recently, surveyors have developed a coil pattern, involving circlesthat gradually shift in the desired direction—a development madepossible with Q-marine single sensor technology. See Biva (208).Compared to prior acquisition patterns, the coil pattern delivered ahigher number of contributions (yellow and red) for a complete range ofazimuths for all offsets. See FIGS. 5A-5E: narrow-azimuth (FIG. 5A),multiazimuth (FIG. 5B), wide-azimuth (FIG. 5C), rich-azimuth (FIG. 5D),coil shooting (FIG. 5E). Further, with parallel geometries, vessels areproductive about 45% of the time, but with a coiled geometry, they areproductive about 90% of the acquisition time.

During pre-processing, positional data gathered in the field is used tocompute a theoretical grid network called a binning grid. Everyindividual recorded seismic trace is assigned to one or more bins; thenumber of traces summed together at each bin is called the fold orcoverage for that bin. The nominal average fold for the survey is partof the descriptive information for the survey. Summing all the tracesassigned to each bin creates a single multi-fold trace that is used asinput to subsequent seismic processing steps. The general rule of thumbis that 3-4 bins are required to map the smallest (narrowest) horizontaldimension of a stratigraphic feature that must be seen in the 3D datavolume. See e.g., FIG. 6. Thus, the geophones in a land-based survey areset at the optimal spacing to allow for 3-4 bin coverage of the smallestfeature to be mapped.

However, in marine surveys, the normal approach is to select the bingrid size based upon the spacing of the sensors in the cables and thespacing of the streamers in the water. Since sensor spacing is fixed atthe time of manufacture, most (if not all) marine seismic surveys areacquired at some multiple 12.5 meters (m). Thus, a common bin size is6.25 m by 25 m or 12.5 m by 12.5 m. If geophysically one only needed a16 m bin grid, the conventional approach would be to oversample at 12.5m. However, this is expensive and wasteful, since these surveys can takemonths to perform. This conventional “racetrack” pattern generates avery uniform distribution of data over the project, but it is wastefulfrom a compressed seismic imaging approach as the survey acquires anexcess of data that is unneeded.

Thus, what is needed in the art is a better method of establishing thebin grid pattern in marine 3D seismic surveys that optimizes dataacquisition over the survey area, and doesn't needlessly cover orover-cover the geological features to be mapped.

SUMMARY OF THE DISCLOSURE

The present disclosure describes a better method of survey design thatavoids or minimizes collecting unneeded data, and allows the vessel tosail with the wind or currents, instead of compensating for same tomaintain straight lines for data collection.

The first step in implementing the disclosure is to select a trial bingrid of a geophysically determined size. Commonly, we determine thissize by bin aliasing rules of the maximum frequency. Conventionalsurveys would then round to the next smaller standard bin size, but inthis disclosure this is no longer necessary.

The next step is to use the geologic model for the project area anddetermine the stability of the Compressed Seismic Imaging (CSI) designsgiven the bin grid and geologic model. While all bin grids will resultin a CSI design for a geologic model, some are not as stable, so it maybe necessary to modify the bin size or orientation and re-determine theCSI design iteratively to locate a stable solution. This process ofestablishing the proper CSI design is addressed in U.S. Pat. No.8,897,094 and US201108011354277, which are incorporated by reference intheir entirety for all purposes.

The next step with the proper designs determined and the offset orsimilar attributes determined, is to establish a set of rules, whichagain will be unique to the region and the CSI algorithm applied. Theserules would be the rules for acquisition and might be, for example, thatin no region more than 3 bins can be missing two unique offset planes ina row or that no more than 15% of the unique offset planes can be voidof traces. The rules would apply to the coverage and distributions ofthe seismic data that will be acquired in the next step and basicallydefine what constitutes a fully acquired dataset. The rules we have usedto date tend to relate to gaps in coverage and orientation anddistribution of the trace data when compared from one bin to another binin the survey and over an areal region.

The next step with the rules in hand is to acquire the seismic data.Because the rules don't require a conventional uniform grid of offsetsand azimuths like a conventional survey, there is no particularrequirement that the survey needs to be acquired in a conventionalracetrack approach or other regular pattern approach. This also impliesthat unlike a conventional survey where it is customary to acquire thedata in a uniform spacing, in the CSI design, the station spacing isnormally not uniform.

There are a few patents like this US20130250720 (random sourceactivation/spacing) and U.S. Pat. No. 8,681,581 (randomizingdistribution of receivers and sources) & U.S. Pat. No. 8,711,654 (randomsurvey locations) that address random style acquisition. CSI techniquesare not random, however, and require that the shots be placed at thepre-determined optimal positions. Simply put CSI approaches have animaging algorithm and technique implicit to their design. Thereforethere exists a single optimal solution for the particular CSI approachapplied that will result in the best image. Many solutions will work butare all sub-optimally. Using a random approach, it is statisticallyunlikely to consistently come up with the optimal solution. Thus, theCSI design approach, while not uniform, is much better than these randomapproaches, which result in a sub-optimal solution.

In actuality, it is likely that the survey would be acquired as a seriesof cross-cutting passes of the vessel at different orientations due toshifting winds, currents, tides and the like. Again, since the surveyoris not required to shoot a racetrack or other regular pattern, there isno reason (unless the rules require it) that the vessel would notacquire the data into and out of the wind for ease of operation or e.g.,with the current. This will be beneficial, because it will allow fastersurveys and reduce noise, which is known be highest when shooting acrosscurrents.

If the winds change, the vessel would just move with the wind. Noefforts need be made to avoid drift off a preset pathway, and instead,the actually pathway is tracked and compared against the desired ruleset to ensure all rules are met. By continuing to shoot until the ruleslaid out above are met and all of the gaps are closed, the concept ofinfill is eliminated. The concept of fighting the currents and tides togenerate a straight racetrack pattern is eliminated and the surveyorjust acquires data without fighting Mother Nature. The conventionalparadigm of marine seismic acquisition is thus obviated and the vesselmeanders according to the wind and currents until the rules are met andfull coverage is obtained.

The concept for this invention was developed while shooting in thearctic and dealing with icebergs, currents, winds and tides.Conventional approaches resulted in a great deal of standby time to findthe exact right conditions where the icebergs were clear of the nexttransit path, while the winds and tides would not force the steamersinto other icebergs. The solution was to acquire the data using theinventive method where one would acquire data in and out of the wind,tide and current direction and then dodge around the icebergs that couldbe drifting in many directions. Icebergs depending on their size can bemoved by different currents at different depths so it is not uncommonfor them to move in oblique directions if one is smaller than the rest.The inventive method allows near continuous acquisition by workingaround the obstacles and working with the winds and current instead ofstanding by waiting for better conditions.

The technical and economic advantage is that this method allows todesign and process surveys that would optimal in terms of costs for therequired geophysics at a significantly cheaper costs than conventionalapproaches, which oversample and collect unneeded data.

As used herein, “design” refers to the precise source and receiverlocations for the data acquired. These locations are determined in theCSI imaging step prior to data acquisition.

By “Compressed Seismic Imaging (CSI) design” herein we mean using thecompressed sensing imaging concepts and apply them specifically toseismic layout, acquisition, and processing and all of the inherentlimitations of seismic data collection like airgun recharge rates andtowing issues etc.

By “stability” herein we refer to the overall mathematical consistencyof a solution or process. A technique that demonstrates stability willconverge on the same answer from many different starting points.

By “stable CSI design,” what is meant is a CSI design that demonstratesstability, e.g., will converge on the same answer from multiple startingpoints.

By “allowing wind and current to direct travel” we mean intentionallyallowing wind and current to direct vessel path at least a significantportion of sailing time, e.g. about 25%, 30%, 40% or so. Thus is to bedistinguished from efforts to travel in a particular grid pattern,wherein the wind and current may occasionally direct travel, but theoperator actively attempts to counteract this, keeping any drifting to aminimum such that a particular survey path, such as racetrack, can beobtained. Thus, accidental wind and current drift is not included underthis understanding of the term.

The use of the word “a” or “an” when used in conjunction with the term“comprising” in the claims or the specification means one or more thanone, unless the context dictates otherwise.

The term “about” means the stated value plus or minus the margin oferror of measurement or plus or minus 10% if no method of measurement isindicated.

The use of the term “or” in the claims is used to mean “and/or” unlessexplicitly indicated to refer to alternatives only or if thealternatives are mutually exclusive.

The terms “comprise”, “have”, “include” and “contain” (and theirvariants) are open-ended linking verbs and allow the addition of otherelements when used in a claim.

The phrase “consisting of” is closed, and excludes all additionalelements.

The phrase “consisting essentially of” excludes additional materialelements, but allows the inclusions of non-material elements that do notsubstantially change the nature of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a side view of a marine seismic survey vessel and seismicwaves.

FIG. 1B is a top view of a typical seismic vessel and streamers.

FIG. 2A-2B show Narrow Azimuth towed streamer (FIG. 2A) andMulti-Azimuth towed streamer (FIG. 2B).

FIG. 3 shows a Multi-Azimuth towed streamers.

FIG. 4 displays the traditional racetrack pattern of acquiring marine 3Dseismic data.

FIGS. 5A-5E compare coverage obtained with various acquisitiongeometries: narrow-azimuth (FIG. 5A), multiazimuth (FIG. 5B),wide-azimuth (FIG. 5C), rich azimuth (FIG. 5D), coil shooting (FIG. 5E).

FIG. 6 shows bin spacing for optimal 3-4 bin coverage of the smallestfeature to be mapped. Geophones are thus set to achieve this binspacing.

DETAILED DESCRIPTION

The disclosure provides novel methods of acquiring seismic data, whicheliminates oversampling, infill and the need to fight wind and currentto provide a straight line data.

Specifically, the methods herein described allow for the design andacquisition of marine seismic surveys using a rule-based mode withoutneed for conventional designs that result in wasted coverage. This willdecrease the cost of acquiring data because of the smaller sampling sizeand ease of determining when enough data has been collected andaccelerate modeling times by decreasing the presence of unneeded datapoints.

The invention includes one or more of the following embodiments, in anycombination thereof:

-   -   A method of acquiring marine 3D seismic data comprising        acquiring 3D data of an area to be surveyed without compensating        for wind and current, but instead allowing wind and current to        direct travel, collecting data positioning data while acquiring        3D data, and continuing until said collected positioning data        indicates that sufficient coverage of said area has been        obtained.    -   A method of marine 3D seismic data acquisition, comprising:        obtaining a marine geology model of a marine survey area;        determining a bin size and orientation based on a smallest        feature to be mapped and a shape of said marine geology model;        determine a stability of a compressed Seismic Imaging (CSI)        design and if unstable modify said source & receiver station        spacing and location, bin size or orientation and re-determine        said stability of said CSI design iteratively to locate a stable        solution for said CSI design; establish a set of rules for        coverage of said marine survey area that meet the CSI design;        and acquiring 3D seismic data over said marine survey area until        said rules are met, wherein wind and current are not compensated        for but allowed to direct vessel travel and or streamer shape at        least a portion of the time.    -   A method of imaging a marine 3D survey area, comprising:        obtaining or developing a geology model of a marine survey area;        determining a bin size and orientation based on a smallest        feature to be mapped and a shape of said marine geology model;        determining a stability of a compressed seismic imaging source        and receiver station and sampling design (“CSI design”), and if        unstable modify said bin size or orientation and re-determine        said stability iteratively to produce a stable CSI design;        establishing a set of sampling rules for coverage of said marine        survey area to assure that appropriate data is recorded so said        stable CSI design can be properly reconstructed; acquiring 3D        seismic data traces over said marine survey area using said        stable CSI design until said rules are met, wherein wind and        current are not compensated for but allowed to direct vessel        travel; reconstructing a wavefield and regularizing the traces        using the appropriate reconstruction techniques to produce        seismic data. In some method, the further steps of processing        the seismic data and imaging the survey area are also included.    -   A method of acquiring marine 3D seismic data comprising:        acquiring 3D seismic data of an marine area to be surveyed        without compensating for wind and current, but instead allowing        wind and current to direct >25% of said travel; collecting data        positioning data while acquiring 3D data; and continuing said        acquiring step until said collected positioning data indicates        that sufficient coverage of said marine area has been obtained        such that a seismic map of said marine area can be constructed        from said 3D seismic data. The wind and current may direct most        of vessel travel, e.g., >50% or >75%, even when shifting.    -   A method as herein described, wherein sufficient coverage is        determined by the following steps: obtaining or developing a        geology model of a marine survey area; determining a bin size        and orientation based on a smallest feature to be mapped and a        shape of said geology model; determining a stability of a CSI        design and if unstable modify said bin size or orientation and        re-determine said stability of said CSI design iteratively to        locate a stable solution and produce a stable CSI design;        establishing a set of sampling rules for coverage of said survey        area to assure that appropriate data is recorded so the CSI        design can be properly reconstructed; and acquiring 3D seismic        data traces over said marine survey area using the stable CSI        design until said rules are met, wherein wind and current are        not compensated for but allowed to direct vessel travel; and        reconstructing a wavefield and regularizing said traces using        appropriate reconstruction techniques to produce seismic data.    -   A method as herein described, including the further step of        processing the seismic data using conventional techniques and        imaging said survey area.    -   A method as herein described, wherein said CSI design is        determined by a method comprising: constructing an optimization        model, via a computing processor, given by        min_(u)∥Su∥₁s.t.∥Ru−b∥₂≤σ wherein S is a discrete transform        matrix, b is seismic data on an observed grid, u is seismic data        on a reconstruction grid, and matrix R is a sampling operator;        defining mutual coherence as:

${\mu \leq \sqrt{\frac{C}{S}\frac{m}{\left( {\log\; n} \right)^{6}}}},$wherein C is a constant, S is a cardinality of Su, m is proportional tonumber of seismic traces on the observed grid, and n is proportional tonumber of seismic traces on the reconstruction grid; deriving a mutualcoherence proxy, wherein the mutual coherence proxy is a proxy formutual coherence when S is over-complete and wherein the mutualcoherence proxy is exactly the mutual coherence when S is a Fouriertransform; and determining a sample grid according to r*=arg minr μ(r).

-   -   A method as herein described, wherein the sample grid is        determined via randomized greedy algorithm method, and/or a        randomized greedy algorithm method finds local minimum.    -   A method as herein described, wherein the sample grid is        determined via a stochastic global optimization method.    -   A method as herein described, wherein r*=arg minr μ(r) is        non-convex.    -   A method as herein described, wherein the mutual coherence proxy        is derived using fast Fourier transform.    -   A method as herein described, wherein collected traces or data        are analyzed in real time or near real time to confirm        sufficient coverage and that said rules have been met.    -   A method as herein described, wherein an actual pathway        travelled is mapped and used to thereby confirm sufficient        coverage and that said rules have been met.    -   Any method described herein, including the further step of        printing, displaying or saving the results of the method.    -   A printout or 3D display of the results of the method.    -   A non-transitory machine-readable storage medium containing or        having saved thereto the seismic imaging results of the method.    -   Any method described herein, further including the step of using        said results in a seismic modeling program to predict e.g.,        reservoir performance characteristics, such as fracturing,        production rates, total production levels, rock failures,        faults, wellbore failure, and the like.    -   Any method described herein, further including the step of using        said results to design and implement a reservoir drilling,        development, production or stimulation program.    -   A non-transitory machine-readable storage medium, which when        executed by at least one processor of a computer, performs the        steps of the method(s) described herein.

The present disclosure also relates to a computing apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes of modeling, or it may comprise ageneral-purpose computer selectively activated or reconfigured by aspreadsheet program and reservoir simulation computer program stored inthe computer. Such computer programs may be stored in a computerreadable storage medium, preferably non-transitory, such as, but is notlimited to, any type of disk including floppy disks, optical disks,CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), randomaccess memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, orany type of media suitable for storing electronic instructions, eachcoupled to a computer system bus.

In one embodiment, the computer system or apparatus may includegraphical user interface (GUI) components such as a graphics display anda keyboard, which can include a pointing device (e.g., a mouse,trackball, or the like, not shown) to enable interactive operation. TheGUI components may be used both to display data and processed data andto allow the user to select among options for implementing aspects ofthe method or for adding information about reservoir inputs orparameters to the computer programs. The computer system may store theresults of the system and methods described above on disk storage, forlater use and further interpretation and analysis. Additionally, thecomputer system may include on or more processors for running saidspreadsheet and simulation programs.

Hardware for implementing the inventive methods may preferably includemassively parallel and distributed Linux clusters, which utilize bothCPU and GPU architectures. Alternatively, the hardware may use a LINUXOS, XML universal interface run with supercomputing facilities providedby Linux Networx, including the next-generation Clusterworx Advancedcluster management system.

Another system is the Microsoft Windows 7 Enterprise or Ultimate Edition(64-bit, SP1) with Dual quad-core or hex-core processor, 64 GB RAMmemory with Fast rotational speed hard disk (10,000-15,000 rpm) or solidstate drive (300 GB) with NVIDIA Quadro K5000 graphics card and multiplehigh resolution monitors.

Slower systems could also be used, but are not preferred because themethod is already compute intensive.

The term “many-core” as used herein denotes a computer architecturaldesign whose cores include CPUs and GPUs. Generally, the term “cores”has been applied to measure how many CPUs are on a giving computer chip.However, graphic cores are now being used to offset the work of CPUs.Essentially, many-core processors use both computer and graphicprocessing units as cores.

Marine Survey Equipment

FIG. 1B shows an overhead view of a marine survey system 100 inaccordance with at least some embodiments of the invention, whereinparavanes are used to control streamer positioning. In particular, FIG.1B shows a survey vessel 102 having onboard equipment 104, such asnavigation, energy source control, and data recording equipment. Surveyvessel 102 is configured to tow one or more sensor streamers 106A-Fthrough the water and one or more sources 130 (one shown here). WhileFIG. 1B illustratively shows six streamers 106, any number of streamers106 may be equivalently used. In other surveys, ocean bottom cables(OBC) or ocean bottom nodes (OBN, cable free receivers) are usedinstead, thus obviating many towed streamer issues.

The streamers 106 are coupled to towing equipment that maintains thestreamers 106 at selected lateral positions with respect to each otherand with respect to the survey vessel 102. The towing equipment maycomprise two paravane tow lines 108A and 108B each coupled to the vessel102 by way of winches 110A and 110B, respectively. The winches enablechanging the deployed length of each paravane tow lines 108. The secondend paravane tow line 108A is coupled to a paravane 112, and the secondend of paravane tow line 108B is coupled to paravane 114. In each case,the tow lines 108A and 108B couple to their respective paravanes throughrespective sets of lines called a “bridle”.

The paravanes 112 and 114 are each configured to provide a lateral force(transverse to the direction of motion) component to the variouselements of the survey system when the paravanes are towed in the water,as will be explained below. The lateral force component of paravane 112is opposed to that of paravane 114. For example, paravane 112 may createa force as illustrated by arrow 116, and the lateral component of force116 is shown by arrow 117. Likewise, paravane 114 may create a force asillustrated by arrow 118, and the lateral component of force 118 isshown by arrow 119. The combined lateral forces of the paravanes 112 and114 separate the paravanes from each other until they put one or morespreader lines 120, coupled between the paravanes 112 and 114, intotension. The paravanes 112 and 114 either couple directly to thespreader line 120, or as illustrated couple to the spreader line by wayof spur lines 122A and 122B.

The streamers 106 are each coupled, at the ends nearest the vessel 102to a respective lead-in cable termination 124A-F. The lead-in cableterminations 124 are coupled to or are associated with the spreaderlines 120 so as to control the lateral positions of the streamers 106with respect to each other and with respect to the vessel 102. It shouldbe noted that the spacings between 106 can be uniform or non-uniformdepending on the CSI implementation chosen. Electrical and/or opticalconnections between the appropriate components in the recording system104 and the sensors (e.g., 109A, 109B) in the streamers 106 may be madeusing inner lead-in cables 126A-F. Much like the tow lines 108associated with respective winches 110, each of the lead-in cables 126may be deployed by a respective winch or similar spooling device suchthat the deployed length of each lead-in cable 126 can be changed.

During periods of time when the survey vessel 102 is traveling in anapproximately straight line, the speed of the paravanes 112 and 114through the water is approximately the same, and thus the lateral forcecreated by similarly configured paravane 112 and 114 may beapproximately the same. However, when the survey vessel 102 executes aturn (e.g., a 180 degree turn to align the vessel for the next pass overthe survey area), the paravane on the outside of the turn tends to movefaster through the water than the paravane on the inside of the turn,the providing greater lateral force than paravane 112. The paravanesalso compensate somewhat for water currents.

The paravanes 112 and 114 can have adjustable lateral force, such thatthe tension on the spreader lines 120 can be controlled. The paravanes112 and 114 according at least some embodiments comprise systems tocontrollably redirect the flow of water past the paravane, and/or adjustthe angle of attack to control the amount of lateral force developed.Angle of attack for purposes of this disclosure and claims shall be arelationship between the direction of motion of the tow vessel 102 and along dimension of one or more frames (described below) of the paravane.

FIG. 1B shows the angle of attack (AoA) for the illustrative situationof FIG. 1A. Such control may be helpful in a variety of situations, suchas during turns.

Compressive Sensing

A common goal of the engineering field of signal processing is toreconstruct a signal from a series of sampling measurements. In general,this task seems impossible because there is no way to reconstruct asignal during the times that the signal is not measured. Nevertheless,with prior knowledge or assumptions about the signal, it turns out to bepossible to perfectly reconstruct a signal from a series ofmeasurements. Over time, engineers have improved their understanding ofwhich assumptions are practical and how they can be generalized.

An early breakthrough in signal processing was the Nyquist-Shannonsampling theorem. It states that if the signal's highest frequency isless than half of the sampling rate, then the signal can bereconstructed perfectly. The main idea is that with prior knowledgeabout constraints on the signal's frequencies, fewer samples are neededto reconstruct the signal.

Around 2004, Emmanuel Candès, Terence Tao, and David Donoho proved thatgiven knowledge about a signal's sparsity, the signal may bereconstructed with even fewer samples than the sampling theoremrequires. This idea is the basis of compressed sensing. Compressivesensing is described in further detail in 61/898,960 filed Nov. 1, 2013,and US20150124560, each incorporated by reference herein in its entiretyfor all purposes. See also U.S. Pat. No. 8,681,581 and US20130250720. Ashort summary is presented herein, and the reader is referred to theabove cases for additional detail.

Compressed sensing is a signal processing technique for efficientlyacquiring and reconstructing a signal, by finding solutions tounderdetermined linear systems. This is based on the principle that,through optimization, the sparsity of a signal can be exploited torecover it from far fewer samples than required by the Shannon-Nyquistsampling theorem. There are two conditions under which recovery ispossible. The first one is sparsity, which requires the signal to besparse in some domain. The second one is incoherence which is appliedthrough the isometric property which is sufficient for sparse signals.

Two classes of optimization models, synthesis- and analysis-basedoptimization models, are considered. For the analysis-based optimizationmodel, a novel optimization algorithm (SeisADM) is presented. SeisADMadapts the alternating direction method with a variable-splittingtechnique, taking advantage of the structure intrinsic to the seismicdata reconstruction problem to help give an efficient and robustalgorithm. SeisADM is demonstrated to solve a seismic datareconstruction problem for both synthetic and real data examples. Inboth cases, the SeisADM results are compared to those obtained fromusing a synthesis based optimization model. Spectral Projected GradientL1 solver (SPGL1) method can be used to compute the synthesis-basedresults.

Through both examples, it is observed that data reconstruction resultsbased on the analysis-based optimization model are generally moreaccurate than the results based on the synthesis-based optimizationmodel. In addition, for seismic data reconstruction, the SeisADM methodrequires less computation time than the SPGL1 method.

Compressive sensing can be successfully applied to seismic datareconstruction to provide a powerful tool that reduces the acquisitioncost, and allows for the exploration of new seismic acquisition designs,such as that described herein. Most seismic data reconstruction methodsrequire a predefined nominal grid for reconstruction, and the seismicsurvey must contain observations that fall on the corresponding nominalgrid points. However, the optimal nominal grid depends on many factors,such as bandwidth of the seismic data, geology of the survey area, andnoise level of the acquired data. It is understandably difficult todesign an optimal nominal grid when insufficient information isavailable. In addition, it may be that the acquired data containpositioning errors with respect to the planned nominal grid. Aninterpolated compressive sensing method is thus presented, which iscapable of reconstructing the observed data on an irregular grid to anyspecified nominal grid, provided that the principles of compressivesensing are satisfied. The interpolated compressive sensing methodprovides an improved data reconstruction compared to results obtainedfrom some conventional compressive sensing methods.

Compressive sensing is utilized for seismic data reconstruction andacquisition design. Compressive sensing theory provides conditions forwhen seismic data reconstruction can be expected to be successful.Namely, that the cardinality of reconstructed data is small under some,possibly over-complete, dictionary; that the number of observed tracesare sufficient; and that the locations of the observed traces relativeto that of the reconstructed traces (i.e. the sampling grid) aresuitably chosen. If the number of observed traces and the choice ofdictionary are fixed, then choosing an optimal sampling grid increasesthe chance of a successful data reconstruction.

To that end, a mutual coherence proxy is considered which is used tomeasure how optimal a sampling grid is. In general, the computation ofmutual coherence is prohibitively expensive, but one can take advantageof the characteristics of the seismic data reconstruction problem sothat it is computed efficiently. The derived result is exact when thedictionary is the discrete Fourier transform matrix, but otherwise theresult is a proxy for mutual coherence. The mutual coherence proxy in arandomized greedy optimization algorithm is used to find an optimalsampling grid, and show results that validate the use of the proxy usingboth synthetic and real data examples.

One example of a computer-implemented method for determining optimalsampling grid during seismic data reconstruction includes: a)constructing an optimization model, via a computing processor, given by:min_(u) ∥Su∥ ₁ s.t.∥Ru−b∥ ₂≤σwherein S is a discrete transform matrix, b is seismic data on anobserved grid, u is seismic data on a reconstruction grid, and matrix Ris a sampling operator; b) defining mutual coherence:

$\mu \leq \sqrt{\frac{C}{S}\frac{m}{\left( {\log\mspace{14mu} n} \right)^{6}}}$wherein C is a constant, S is a cardinality of Su, m is proportional tonumber of seismic traces on the observed grid, and n is proportional tonumber of seismic traces on the reconstruction grid; c) deriving amutual coherence proxy, wherein the mutual coherence proxy is a proxyfor mutual coherence when S is over-complete and wherein the mutualcoherence proxy is exactly the mutual coherence when S is a Fouriertransform; and d) determining a sample grid:r _(*)=arg min_(r)μ(r)In some embodiments, the sample grid is determined via randomized greedyalgorithm method, and the randomized greedy algorithm method finds localminimum. In others, the sample grid is determined via stochastic globaloptimization method. In still other embodiments, r_(*)=arg min_(r)μ(r)is non-convex. In yet others, the mutual coherence proxy is derivedusing fast Fourier transform.

Data Acquisition Method

In rule-based modeling, a set of rules is used to indirectly specify amathematical model. The rule-set can either be translated into a modelsuch as Markov chains or differential equations, or be treated usingtools that directly work on the rule-set in place of a translated model,as the latter is typically much bigger. Rule-based modeling isespecially effective in cases where the rule-set is significantlysimpler than the model it implies, meaning that the model is a repeatedmanifestation of a limited number of patterns.

The present method establishes an independent bin grid of somegeophysically selected size that is used to determine the neededlocations of the source and receivers to properly populate the area toobtain an accurate image of the data. Once the locations are determined,specific project rules for the seismic acquisitions can be developed andapplied in the field to determine if additional data needs to beacquired. Thus, only the needed data is acquired, and expense is savedin avoiding over-acquiring excess data.

The first step to implementing the method is to select a trial bin gridof a geophysically determined size. Bin grids are created during seismictrace processing by calculating the theoretical common mid point(usually called CMP) locations for each shot-receiver pair and thensumming the traces together based on a mathematical gridding algorithm.Thus, the size of the bin grid is based upon the spacing of the sensorsin the cables and the spacing of the streamers in the water. When thebin grid size matches the area of interest, then an appropriate amountof sampling is obtained. However, for larger or smaller areas,oversamples occurs resulting in the accumulation of unnecessary datapoints the slow down processing and analysis of the seismic data.

The geologic model for the selected trial bin grid is used to estimatethe stability of a Compressed Seismic Imaging (CSI) design. Using priorknowledge of the likely geology in the targeted region an overallgeologic model is constructed. Using the sampling spacings or stationlayouts is then tested against the proposed CSI design to test thestability of the solution. This process is effectively repeated for allpossible CSI approaches for the particular design and then the bestsampling is selected that results in the maximum mutual incoherence.

Once the proper design and their offsets are determined, rules can bedeveloped. The set of rules will be unique to the chosen region and tothe CSI algorithm that is applied, but in effect are a measure of howbadly can the data be sampled and still properly reconstruct the correctwavefield and image. These rules mainly cover the rules for acquisitionof data, such as no region greater than 3 bins can be missing two uniqueoffset planes in a row. Other rules relating to gaps in coverage ororientation of the shot/receivers and/or distribution of the trace datacan also be developed. These rules are necessary to make sure that theminimum required data to properly reconstruct the wavefield using CSItechniques are collected in the field. The normal approach for creationof the rules is to take the perfectly acquired CSI design and then startdecimating various attributes like sampling until the final imagedegrades. In the chosen example of 3 bins in a row missing 2 uniqueoffset planes, depending on the CSI design, if 3 unique offset planes ina row are missing data then the solution is degraded and an artifact inthe final process image is created. This creates a rule that whenacquiring the data must be met or acquisitions continue until it is metand the survey is completed.

Unlike a conventional marine survey, the rules-based method does notrequire a uniform grid of offsets and azimuths. Thus, the survey can becollected using whichever pattern is quickest, cheapest, and mostreliable. Series or cross-cutting passes of the vessel at differentorientations due to winds and tides are expected to be the best patternfor collecting data.

If winds change, the surveying ship can simply move with the windinstead of trying to maintain a set pattern such as the racetrackapproach. Thus, time and money can be saved by utilizing nature tocollect data instead of fighting currents and tides to adhere to a rigidcollection pattern. In effect, although the ship may attempt to collectthe data is some predetermined pattern, it need not stick to thatpattern as wind and current change are not problematic, thus, a degreeof meandering can be tolerated, and even a high degree of what appearsto be meandering. However, from the view-point of the data acquisition,the operator will not be meandering but simply driving where needed tocover the field, and not fighting wind and currents to do so.

By continuing to shoot until the rules are met, the resulting surveywill have no gaps and no infill, or at least un-needed infill will besubstantially reduced. This will aid in reducing modeling time and cost.On the other hand, there may be areas where there is a surplus of dataacquired because of the way the tides and winds worked out. Theseoversampled areas are a byproduct of not standing by for weather andwinds and follow the goal of excess data is better than no data andpaying to wait on weather.

In order to know that sufficient coverage has been obtained to meet therules, the data will either be analyzed in real time or near real time,or one can track the actual pathway travelled, and thereby confirmsufficient coverage.

A variety of commercially available acquisition and tracking programscan be used herein. See e.g., the Omni 3D Design package, NORSAR-3Dmodeling package, the Nucleus software package, Globe claritas, Delph,Seismix, and the like.

While the invention is described above in detail, it should beunderstood that various changes, substitutions, and alterations can bemade without departing from the spirit and scope of the invention asdefined by the following claims. Those skilled in the art may be able tostudy the preferred embodiments and identify other ways to practice theinvention that are not exactly as described herein. It is the intent ofthe inventors that variations and equivalents of the invention arewithin the scope of the claims while the description, abstract anddrawings are not to be used to limit the scope of the invention. Theinvention is specifically intended to be as broad as the claims belowand their equivalents.

The following references are incorporated by reference in theirentirety.

-   Buia M. et al., Shooting Seismic Surveys in Circles, Oilfield    Review, Autumn 2008:18-31.-   Wang Y., Recovery of Seismic Wavefields Based on Compressive Sensing    by an 11-Norm Constrained Trust Region Method and the Piecewise    Random Sub-sampling Geophys. J. Int. (2010) 000, 1-19.-   61/898,960, filed Nov. 1, 2013, and US20150124560 Compressive    sensing-   US20100265799 Compressive sensing system and method for bearing    estimation of sparse sources in the angle domain-   U.S. Pat. No. 8,681,581 Randomization of data acquisition in marine    seismic and electromagnetic acquisition-   US20130250720 Method for acquiring marine seismic data-   U.S. Pat. No. 8,711,654 Random sampling for geophysical acquisitions-   U.S. Pat. No. 8,897,094 L Marine seismic data acquisition using    designed non-uniform streamer spacing-   US201108011354277-   WO2012166737 Two-way wave equation targeted data selection for    seismic acquisition of complex geologic structures-   US2012300585 Reciprocal method two way wave equation targeted data    selection for seismic acquisition of complex geologic structures-   US20120014212 Continuous composite relatively adjusted pulse-   U.S. Pat. No. 5,079,703 3-dimensional migration of irregular grids    of 2-dimensional seismic data

What is claimed is:
 1. A method of imaging a marine 3D survey area,comprising: a) obtaining a geology model of a marine survey area; b)determining a bin size and orientation based on a smallest feature to bemapped and a shape of a marine geology model; c) determining a stabilityof a compressed seismic imaging source and receiver station and samplingdesign (“CSI design”), and if unstable modify said bin size ororientation and re-determine said stability iteratively to produce astable CSI design; d) establishing a set of sampling rules or criteriafor coverage of said marine survey area to assure that appropriate datais recorded so said stable CSI design can be properly reconstructed; e)acquiring 3D seismic data traces over said marine survey area allowingwind and marine current to direct at least a portion of vessel travel,wherein said 3D seismic data traces are acquired over said marine surveyarea until said sampling rules or criteria are satisfied; f)reconstructing a wavefield and regularizing 3D seismic data traces usingreconstruction techniques to produce seismic data; and g) processingsaid seismic data and imaging said survey area.
 2. A method of acquiringmarine 3D seismic data comprising: a) acquiring 3D seismic data of amarine area to be surveyed allowing wind and marine current to direct atleast twenty five percent (25%) of vessel travel; b) collectingpositioning data while acquiring 3D data; and c) continuing step a)until said collected positioning data indicates that sufficient coverageof said marine area satisfies a predetermined set of sampling rules orcriteria.
 3. The method of claim 2, wherein the predetermined set ofsampling rules or criteria include: a) obtaining a geology model of amarine survey area; b) determining a bin size and orientation based on asmallest feature to be mapped and a shape of said geology model; c)determining a stability of a CSI design and if unstable modify said binsize or orientation to produce a stable CSI design; d) establishing aset of sampling rules or criteria for coverage of said survey area toassure that appropriate data is recorded so said stable CSI design canbe properly reconstructed.
 4. The method of claim 3, including thefurther step of processing the seismic data using conventionaltechniques and imaging said survey area.
 5. The method of claim 3,wherein said CSI design is determined by a method comprising: a)constructing an optimization model, via a computing processor, given byminu∥Su∥₁s.t.∥Ru−b∥₂≤σ wherein S is a discrete transform matrix, b isseismic data on an observed grid, u is seismic data on a reconstructiongrid, and matrix R is a sampling operator; b) defining mutual coherenceas:${\mu \leq \sqrt{\frac{C}{S}\frac{m}{\left( {\log\; n} \right)^{6}}}},$wherein C is a constant, S is a cardinality of Su, m is proportional tonumber of seismic traces on said observed grid, and n is proportional tonumber of seismic traces on said reconstruction grid; c) deriving amutual coherence proxy, wherein said mutual coherence proxy is a proxyfor mutual coherence when S is over-complete and wherein said mutualcoherence proxy is exactly said mutual coherence when S is a Fouriertransform; and d) determining a sample grid according to r*=arg minrμ(r).
 6. The method of claim 4, wherein said sample grid is determinedvia a randomized greedy algorithm method.
 7. The method of claim 4,wherein said sample grid is determined via a randomized greedy algorithmmethod and said randomized greedy algorithm method finds local minimum.8. The method of claim 4, wherein said sample grid is determined via astochastic global optimization method.
 9. The method of claim 4, whereinr*=arg minr μ(r) is non-convex.
 10. The method of claim 4, wherein saidmutual coherence proxy is derived using a fast Fourier transform. 11.The method of claim 1, wherein data is analyzed in real time or nearreal time to confirm sufficient coverage and that said rules or criteriahave been met.
 12. The method of claim 1, wherein an actual pathwaytravelled is mapped and used to thereby confirm sufficient coverage andthat said rules or criteria have been met.
 13. A non-transitorymachine-readable storage medium carrying computer executableinstructions for imaging a marine survey area, which when executed by atleast one processor of a computer, implement: acquiring 3D seismic dataof a marine area to be surveyed allowing wind and marine current todirect at least twenty five percent (25%) of vessel travel; collectingpositioning data while acquiring 3D data; continuing step a) until saidcollected positioning data indicates that coverage of said marine areasatisfies a predetermined set of sampling rules; wherein an actualpathway travelled is mapped and used to thereby confirm sufficientcoverage and that said rules have been met.
 14. A non-transitorymachine-readable storage medium carrying computer executableinstructions for imaging a marine survey area, which when executed by atleast one processor of a computer, implement: obtaining or developing ageology model of a marine survey area; determining a bin size andorientation based on a smallest feature to be mapped and a shape of amarine geology model; determining a stability of a compressed seismicimaging source and receiver station and sampling design (“CSI design”),and if unstable modify said bin size or orientation and re-determinesaid stability iteratively to produce a stable CSI design; establishinga set of sampling rules or criteria for coverage of said marine surveyarea to assure that appropriate data is recorded so said stable CSIdesign can be properly reconstructed; acquiring 3D seismic data tracesover said marine survey area allowing wind and marine current to directat least a portion of vessel travel, wherein said said 3D seismic datatraces are acquired over said marine survey area until said samplingrules or criteria are satisfied.